Hi fam!
It's easy to get distracted by the latest AI headlines.
But the real question isn't what AI can do anymore.
It's how you use it.
Today, we're covering the latest AI news, a simple technique for getting better first drafts, how to build an AI knowledge base that saves hours of work, and a reminder that while AI can create content, your perspective is still what makes it worth reading.
Let's get started. 🚀
The future of AI feels Like Magic, and it’s here!
This past days showed again that the future of AI isn't just about building smarter models—it's about securing billions in funding, navigating new regulations, and finding enough power to keep those models running.
Google has postponed the launch of Gemini 3.5 Pro, reportedly to improve its coding performance and overall quality before release. The delay has fueled speculation that competition from OpenAI, Anthropic, and Meta is putting increasing pressure on Google.
Why this matters: In today's AI race, shipping first isn't always the winning strategy. Companies are increasingly delaying releases rather than launching models that aren't ready.
The European Commission has ordered Google to make parts of Android and Search available to competing AI assistants under the Digital Markets Act. The move aims to make it easier for rivals to compete with Google's built-in AI services.
Why this matters: AI competition is no longer just about better models—it's also about who gets access to users and platforms.
Apple has expanded public access to its AI-powered Siri beta as it continues integrating generative AI across its ecosystem. The rollout is part of Apple's broader effort to catch up with competitors in consumer AI.
Why this matters: Apple is gradually bringing AI to millions of existing users instead of launching a standalone chatbot, showing a very different strategy from OpenAI or Anthropic.
Chinese AI startup DeepSeek is reportedly in talks to raise $1.5 billion at a valuation of around $71 billion, with plans to pursue an IPO afterward. The fresh funding would primarily be used to expand computing infrastructure and accelerate the development of future AI models.
Why this matters: Just a year ago, DeepSeek shocked the AI industry with powerful open models built on a fraction of the budget of its U.S. competitors. Now, it's proving that even the most efficient AI companies eventually need billions of dollars to stay competitive. The AI race isn't just about smarter models anymore—it's also about who can afford the compute to build the next generation.
New York has become the first U.S. state to impose a one-year moratorium on new hyperscale AI data centers, temporarily halting permits for facilities using 50 MW or more of power. State officials say the pause will give them time to create new standards for electricity use, water consumption, environmental impact, and local infrastructure before approving more projects.
Why this matters: For the first time, AI isn't being slowed by a lack of better models—it's being slowed by the infrastructure needed to run them. The debate is shifting from "How powerful can AI become?" to "Can our power grids, water supplies, and communities support it?" As AI demand grows, access to compute and energy may become just as important as breakthroughs in the models themselves.
Ask for Version 2 First
Asking AI for a "first draft" is like letting a toddler paint your living room. Sure, there’s paint on the walls, but now you have to spend hours cleaning up the mess. Instead of playing cleanup crew for a mediocre draft, try this:
"Skip the first draft. Show me what Version 2 would look like."
This simple prompt encourages AI to move past the most obvious ideas and deliver something more polished, creative, and refined from the start.
Example:
"Write a LinkedIn post announcing our new AI course," go with a much better version: "Write a LinkedIn post announcing our new AI course. Skip the first draft and show me what Version 2 would look like. Make it sound confident, conversational, and avoid generic marketing phrases."
You'll often get stronger writing, better headlines, smarter ideas, and fewer clichés—without the extra back-and-forth.
Sometimes the fastest way to a great first draft... is asking for the second one first.
Build Your Own Personal AI Knowledge Base
Have you ever noticed that using AI sometimes feels like training a new intern every single morning?
You open a new chat. You upload the same three PDFs. You paste your company’s brand guidelines, explain your project’s goals for the hundredth time, and then—finally—you get to ask your actual question.
It’s exhausting. It’s repetitive. And frankly, it’s a massive waste of your cognitive bandwidth.
What if you only had to explain yourself once?
Stop Starting from Scratch: Meet NotebookLM
Most people treat AI like a search engine—a blank slate that forgets who you are the moment you close the tab.
But the real productivity hack is building a Personal AI Knowledge Base.
Using tools like Google’s NotebookLM, you can upload your PDFs, Google Docs, website links, meeting transcripts, and even YouTube videos into one dedicated space.
The Difference: It’s like having ChatGPT, but instead of being trained on the entire, chaotic internet, it is trained exclusively on your data.
How It Works in the Real World
Let's say you're gearing up for a major product launch. Instead of digging through ten different folders every time you need an answer, you drop everything into your notebook:
Your Inputs: Product docs, marketing strategy, competitor analysis, and last week's raw meeting notes.
The Magic: Once uploaded, you stop searching and start prompting.
Instead of hunting for files, you simply ask the AI:
"What are the top three features our beta testers are actually complaining about?"
"Create a 5-step launch checklist based on my meeting notes and the marketing strategy."
"Are there any contradictions between our technical documentation and our sales deck?"
AI does the heavy lifting, connecting the dots across dozens of files in seconds.
The Ultimate Productivity Shift
The biggest leap in AI productivity isn't learning how to write faster prompts. It’s never having to explain the same context twice.
As you work, your knowledge base grows with you. Every new document you upload makes it smarter. Every past project becomes instantly searchable.
You aren't just chatting with a bot anymore—you’re collaborating with a digital teammate that already knows your business inside and out.
Your homework for this week: Go to NotebookLM, drop in 3 to 5 documents from your current project, and ask it to summarize the key action items. You’ll never go back to a blank prompt screen again. 🚀
From The Archive: How to Use AI to Create a Money-Making Newsletter for Your Business
Back in 2024, we explored how AI could help anyone start a newsletter. It could speed up research, generate ideas, write drafts, and make publishing feel far less intimidating.
Fast forward two years, and AI has become even more capable. It can brainstorm topics, analyze trends, create images, edit copy, optimize headlines, translate content, and even help automate your entire publishing workflow.
But here's what hasn't changed.
The newsletters people actually look forward to reading aren't the ones that use the most AI. They're the ones with a clear voice, consistent quality, and a unique perspective that readers can't get anywhere else.
AI has made creating content easier than ever. Standing out, however, still depends on trust, experience, and having something genuinely worth saying.
That's a lesson that's just as true today as it was in 2024.
Text generation | Image Generation | LMAI recommends |
|---|---|---|
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